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\title{Statement of Research Interest}
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\author{Jie Bao}

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\begin{comment}

Neuroscience is a huge challenge that people are facing today. Being a biologist
and having done experiments myself, I came to the realization that there are
far too many questions that experiments cannot answer, simply due to various 
kinds of technical limitations. Therefore I would like to apply well-established
theoretical approaches in mathematics and physics to study the brain 
quantitatively, through
which I hope to elucidate, reconstruct the experimental results and make 
reasonable predictions for the future work as well.
One of the theoretical methods to study the brain is to construct a 
computational model and
track its behavior in numerical simulations. With the advance of computer
resources, the simulation of large-scale spiking neuronal networks is now
feasible and thus becomes a key tool in the research.

Among the different aspects of neuronal networks, I am most interested in the 
interplay between structure and dynamics,
since the structure of neuronal networks must subserve their functions. 
Far from being a 
random graph, we now know that the brain, esp. the neocortex, is organized
in a specific fashion. How this network topology becomes optimized and 
determines the network activity is one of the questions, into which I would like to 
gain some insight.

Understanding how the brain works can not only benefit the neuroscience
community, but it can facilitate the application of novel technologies as well.
For instance, it is interesting to build an integrated-circuit implementation of 
the whole or part of the brain. In other words, instead of simulating the brain
using a certain software, one can emulate the brain by building a 
hardware that functions exactly the same.
Furthermore, if a robot adopts the algorithm that the brain uses,
the robot is supposed to interact with the environment and the people in a more
human-like manner.
The hope that one
is able to transfer what we learned in the neuronal network simulation to the 
silicon and robotic level looks quite promising to me and I certainly would not 
hesitate to work on that. 


Neuroscience is a huge challenge that people are facing today. Although 
having investigated for decades, people still only have a vague idea of how 
the brain works. One of the questions to be addressed is how the brain 
integrates all sensory information and previous experience and memory to 
make a decision, which is also believed to involve a large-scale brain area 
and a complex neunonal network. Thanks to the modern imaging techniques, one
is now able to study the hemodynamic changes as a signal of the whole brain activity
during certain behavioral tasks.

Among the different aspects of neuroscience, I am most interested in the 
interplay between structure and dynamics in the brain,
since the structure of neuronal networks must subserve their functions. 
Far from being a 
random graph, we now know that the brain, esp. the neocortex, is organized
in a specific fashion. How this network topology becomes optimized and 
determines the network activity, how different regions of the brain interact
with each other is one of the questions, into which I would like to 
gain some insight.

My other interest lies in the learning rules that the brain adapts. 
Through studying the roles that different brain areas play 
during decision making, I hope to eventually come up with a model of making a
certain choice, which can ideally explain how learning is incoporated in the 
network and hopefully even predict the behavior of individuals under 
certain circumstances.

\end{comment}

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\section*{Names of Referees}

\begin{itemize}
\item Felix Sch\"urmann

EPFL AI BBP\\
AAB 1 14 (B$\hat{a}$timent AAB)\\
Station 15\\
CH-1015 Lausanne\\
Switzerland\\

+41 21 6939647

felix.schuermann@epfl.ch

\item Ad Aertsen
\begin{verbatim}
 Neurobiology and Biophysics                   Bernstein Center for
 Institute of Biology III                Computational Neuroscience
 www.brainworks.uni-freiburg.de            www.bccn.uni-freiburg.de
 Albert-Ludwigs-University                 Tel:  +49 (761) 203 2718
 Schaenzlestrasse 1                        Secr: +49 (761) 203 2786
 D-79104 Freiburg i.Br.                    Fax:  +49 (761) 203 2860
 Germany

ad.aertsen@biologie.uni-freiburg.de
\end{verbatim}
\end{itemize}

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